Introduction
Over 40% of U.S. older adults have obesity1 and could be eligible for treatment with glucagon-like peptide-1 (GLP-1) or dual GLP-1/glucose-dependent insulinotropic polypeptide (GIP) receptor agonists (hereafter GLPs) to provide effective weight loss and improve obesity-related outcomes.2 However, few participants enrolled in pivotal clinical trials supporting U.S. Food and Drug Administration (FDA) approval of GLPs for obesity were age ≥65 years.3 To understand whether low older adult enrollment was due to restrictive trial eligibility criteria, we estimated the percentage of older Medicare beneficiaries who would be excluded from GLP pivotal trials.
Methods
We utilized the Medicare Current Beneficiary Survey (MCBS) 2021 survey file and corresponding claims datasets to identify Medicare beneficiaries aged ≥65 years with a body mass index of ≥30 kg/m2. To apply pivotal trial exclusion criteria to this cohort, we first identified 9 pivotal trials from FDA approval packages within the Drugs@FDA database for all 3 GLPs approved for obesity (liraglutide, semaglutide, tirzepatide). Exclusion criteria were extracted from trial protocols linked to publications. Exclusion criteria were then applied if present in all pivotal trials for a given medication, not temporary (existing for 6 months or less), defined by International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes from claims or from survey responses within the MCBS, and not related to childbearing. Depression, non-skin cancer, and type 1 diabetes definitions utilized both ICD-10 codes and survey responses, while all other criteria utilized only ICD-10 codes. Due to multiple possible operationalized definitions of depression, we utilized a narrow (ICD-10 code or Patient Health Questionaire-9≥15) and broad (narrow criteria or reporting ever having depression) definition.
We first characterized the Medicare beneficiary sample by size as well as age, sex, and race and ethnicity. We then calculated the percentage of participants who would have met exclusion criteria for pivotal trials for each medication. Survey weights were applied to account for the complex MCBS design. Analyses were performed using R version 4.2.1 (2022-06-23). The Yale University Institutional Review Board deemed this study not human subjects research. We followed the STROBE reporting guideline.
Results
There were 2,978 Medicare beneficiaries aged ≥65 years with a body mass index of ≥30 kg/m2 (mean age of 75 [SD 6.8]; 56.7% female; 0.4% Asian, 11.2% Black, 4.4% Hispanic, 80.3% White, and 3.7% other race/ethnicity), representing 15,285,883 older adults with obesity. Utilizing a narrow definition of depression, 27.1% (95% CI 25.6–28.6) older Medicare beneficiaries with obesity who would have been excluded; 25.8% (95% CI 24.4%−27.2%) for liraglutide trials, 26.1% (95% CI 24.7%−27.5%) for semaglutide trials, and 26.9% (95% CI 25.4%−28.4%) for tirzepatide trials. Men and women met exclusion criteria at similar prevalences. Patients meeting exclusion criteria were older and more often of Asian or unknown race/ethnicity (Table 1). Utilizing a broad definition of depression, 44.9% (95% CI 43.0–46.8) of older Medicare beneficiaries with obesity would have been excluded. The most common reasons for exclusion were depression and non-skin cancer. (Table 2)
Table 1:
Demographic characteristics of older Medicare beneficiaries with obesity who did and did not meet exclusion criteria for GLP pivotal trials based on Medicare Current Beneficiary Survey using narrow depression definition, N = 15,285,883
| Met exclusion criteria (N = 4,137,121) |
Did not meet exclusion criteria (N = 11,148,763) |
Overall (N = 15,285,883) |
P-valuea | |
|---|---|---|---|---|
| Gender | ||||
| Female | 2,356,613 (27.39%) | 6,246,046 (72.61%) | 8,602,660 | 0.55 |
| Male | 1,780,507 (26.64%) | 4,902,716 (73.36%) | 6,683,224 | |
| Age | ||||
| 65–74 | 2,588,709 (25.92%) | 7,399,394 (74.08%) | 9,988,104 | 0.02 |
| 75–84 | 1,297,493 (28.92%) | 3,189,148 (71.08%) | 4,486,641 | |
| 85+ | 250,919 (30.93%) | 560,220 (69.07%) | 811,139 | |
| Race/ethnicity | ||||
| American Indian or Alaska Native | 6,648 (7.06%) | 87,557 (92.94%) | 94,205 | 0.001 |
| Asian | 47,340 (43.44%) | 61,632 (56.56%) | 108,972 | |
| Black | 527,096 (27.23%) | 1,408,522 (72.77%) | 1,935,618 | |
| Hispanic | 72,980 (15.15%) | 408,792 (84.85%) | 481,772 | |
| White | 3,304,342 (27.30%) | 8,798,954 (72.70%) | 12,103,296 | |
| Other | 33,109 (19.15%) | 139,819 (80.85%) | 172,928 | |
| Unknown | 145,606 (37.42%) | 243,486 (62.58%) | 389,092 |
Comparisons based on chi-squared tests using complex survey design
Table 2:
Prevalence of older adult beneficiaries with obesity meeting exclusion criteria from GLP pivotal trials based on Medicare Current Beneficiary Survey, N = 15,285,883
| Exclusion Criteria | Liraglutide % (95% CI) | Semaglutide % (95% CI) | Tirzepatide % (95% CI) |
|---|---|---|---|
| Any exclusion (narrow depression definition) | 25.79 (24.43–27.20) | 26.05 (24.67–27.47) | 26.89 (25.42–28.42) |
| Any exclusion (broad depression definition) | 43.87 (42.04–45.73) | 44.03 (42.17–45.90) | 44.74 (42.83–46.67) |
| Depression (narrow)a | 4.64 (4.02–5.35) | 4.64 (4.02–5.35) | 4.64 (4.02–5.35) |
| Depression (broad)b | 28.05 (26.42–29.74) | 28.05 (26.42–29.74) | 28.05 (26.42–29.74) |
| Cancer (non-skin) | 19.95 (18.91–21.03) | 19.95 (18.91–21.03) | 19.95 (18.91–21.03) |
| Type 1 diabetes | 1.61 (1.29–2.00) | 1.61 (1.29–2.00) | 1.61 (1.29–2.00) |
| Renalc | NAd | 0.65 (0.40–1.03) | 1.22 (0.87–1.70) |
| Substance use disordere | 0.37 (0.24–0.58) | 0.37 (0.24–0.58) | NA |
| Acute or chronic hepatitis not related to NAFLDf | NA | NA | 0.74 (0.51–1.07) |
| Severe psychiatric disordersg | 0.35 (0.21–0.56) | 0.35 (0.21–0.56) | 0.35 (0.21–0.56) |
| Condition that interferes with hemoglobin A1c testingh | NA | NA | 0.18 (0.09–0.34) |
| Prior organ transplant | NA | NA | 0.10 (0.04–0.26) |
| Acute pancreatitis | 0.10 (0.03–0.27) | NA | 0.10 (0.03–0.27) |
| Prior bariatric surgery | 0.08 (0.03–0.22) | 0.08 (0.03–0.22) | 0.08 (0.03–0.22) |
| Proliferative diabetic retinopathy | 0.47 (0.27–0.82) | 0.47 (0.27–0.82) | 0.47 (0.27–0.82) |
| Gastroparesis | NA | NA | 0.05 (0.02–0.16) |
| Chronic pancreatitis | 0 | 0 | 0 |
| Familial MEN2 | NA | 0.02 (0.00–0.07) | NA |
| MEN2 | NA | 0 | 0 |
| Endocrinopathies or genetic conditions causing obesityi | 0 | NA | 0 |
| Suicidal ideation | 0 | 0 | 0 |
Narrow depression definition - ICD-10 criteria for depression, or scoring a PHQ-9≥15
Broad depression definition – ICD-10 criteria for depression, answering yes to ever having depression, or scoring a PHQ-9≥15
Renal exclusion criteria for semaglutide were chronic kidney disease stage 5 and end stage renal disease. Renal exclusion criteria for tirzepatide were chronic kidney disease stages 4–5 and end stage renal disease.
NA – exclusion criterion not applicable to this drug
Included alcohol use disorder, opiate use disorder, sedative use disorder, cocaine use disorder, stimulant use disorder, hallucinogen use disorder, and inhalant related disorders
NAFLD – non-alcoholic fatty liver disease
Severe psychiatric disorders – bipolar disorder, schizophrenia, or psychosis
Conditions that interfered with hemoglobin A1c testing - sickle cell disorders, hereditary hemolytic anemias, acquired hemolytic anemia
Endocrinopathies or genetic conditions causing obesity – Cushing syndrome, Bardet-Biedl, Prader-Willi
Conclusions
In this cross-sectional analysis of older Medicare beneficiaries with obesity, 27.1% to 44.9% of older adults would be ineligible for pivotal trial participation due to one or more exclusion criteria, varying based on the definition used for depression. This suggests that exclusion criteria, particularly depression and prior cancer, may contribute to under enrollment of older adults in GLP trials.
Our analyses utilizing claims data to examine generalizability of GLP trials to older Medicare beneficiaries provide similar estimates to a previous study based on national survey data for adults ≥60.4 However, the true exclusion rate of older adults from GLP pivotal trials may depend on how investigators operationalized depression as part of the exclusion criteria. A limitation of this study is that claims may underestimate the prevalence of certain conditions, thus leading to an underestimate of pivotal trial exclusion.
Recent FDA guidance requires sponsors to submit diversity action plans with enrollment targets and plans for enrolling participants across demographics including age, which may improve the enrollment of older adults in future obesity treatment trials.5 To enable generation of robust evidence among older Medicare adults, the Centers for Medicare & Medicaid Services could provide coverage of GLPs for obesity under the “Coverage with Evidence Development” program, which requires beneficiaries to participate in clinical studies.6
Acknowledgements:
Dr. Chen was supported by the National Clinician Scholars Program.
Funding declaration:
Dr. Chen is supported by NIH T32 AG019134.
Conflicts of Interest:
Dr. Lipska receives support from CMS to develop and evaluate publicly reported quality measures and royalties from UpToDate to write and edit content.
Dr. Ross currently receives research support through Yale University from Johnson and Johnson to develop methods of clinical trial data sharing, from the Food and Drug Administration for the Yale-Mayo Clinic Center for Excellence in Regulatory Science and Innovation (CERSI) program (U01FD005938), from the Agency for Healthcare Research and Quality (R01HS022882), and from Arnold Ventures; formerly received research support from the Medical Device Innovation Consortium as part of the National Evaluation System for Health Technology (NEST); and in addition, Dr. Ross was an expert witness at the request of Relator’s attorneys, the Greene Law Firm, in a qui tam suit alleging violations of the False Claims Act and Anti-Kickback Statute against Biogen Inc. that was settled September 2022.
Dr Ramachandran reported receiving grants from Arnold Ventures, Stavros Niarchos Foundation, and the US Food and Drug Administration (FDA); receiving personal fees from the Roosevelt Institute and previously, the ReAct-Action on Antibiotic Resistance Strategy Policy Program in 2022; and serving on the board of directors for Doctors for America in an unpaid capacity outside the submitted work.
Footnotes
Dr. Chen has no conflicts of interest to disclose.
Ms. Liang has no conflicts of interest to disclose.
Data Availability:
The datasets during and/or analyzed during the current study are available from the corresponding author on reasonable request.
References
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Associated Data
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Data Availability Statement
The datasets during and/or analyzed during the current study are available from the corresponding author on reasonable request.